/*--------------------------------------------------------*/
void AzOptOnTree::_refreshPred_TempFile()
{
if (v_w.rowNum() == 0 && v_p.rowNum() == 0) return;
v_p.zeroOut();
v_p.set(var_const+fixed_const);
const double *w = v_w.point();
int tree_num = ens->size();
int tx;
for (tx = 0; tx < tree_num; ++tx) {
ens->tree_u(tx)->restoreDataIndexes();
AzIIarr iia_nx_fx;
tree_feat->featIds(tx, &iia_nx_fx);
int num = iia_nx_fx.size();
int ix;
for (ix = 0; ix < num; ++ix) {
int nx, fx;
iia_nx_fx.get(ix, &nx, &fx);
if (tree_feat->featInfo(fx)->isRemoved) continue;
int dxs_num;
const int *dxs = data_points(fx, &dxs_num);
updatePred(dxs, dxs_num, w[fx], &v_p);
}
ens->tree_u(tx)->releaseDataIndexes();
}
}
/*--------------------------------------------------------*/
void AzOptOnTree::_update_with_features_TempFile(
double nlam,
double nsig,
double py_avg,
AzRgf_forDelta *for_del) /* updated */
{
int tree_num = ens->size();
int tx;
for (tx = 0; tx < tree_num; ++tx) {
ens->tree_u(tx)->restoreDataIndexes();
AzIIarr iia_nx_fx;
tree_feat->featIds(tx, &iia_nx_fx);
int num = iia_nx_fx.size();
int ix;
for (ix = 0; ix < num; ++ix) {
int nx, fx;
iia_nx_fx.get(ix, &nx, &fx);
if (tree_feat->featInfo(fx)->isRemoved) continue; /* shouldn't happen though */
double w = v_w.get(fx);
int dxs_num;
const int *dxs = data_points(fx, &dxs_num);
double my_nlam = reg_depth->apply(nlam, node(fx)->depth);
double my_nsig = reg_depth->apply(nsig, node(fx)->depth);
double delta = getDelta(dxs, dxs_num, w, my_nlam, my_nsig, py_avg, for_del);
v_w.set(fx, w+delta);
updatePred(dxs, dxs_num, delta, &v_p);
}
ens->tree_u(tx)->releaseDataIndexes();
}
}
int main(int argc, char** argv) {
if (argc > 1) {
srand(atoi(argv[1]));
} else {
srand(time(NULL));
}
// gnuplot: plot 'data_points.dat', 'hull_points.dat' with lines
DATA_POINTS_FILE = fopen("data_points.dat", "w");
HULL_POINTS_FILE = fopen("hull_points.dat", "w");
assert(DATA_POINTS_FILE != NULL);
assert(HULL_POINTS_FILE != NULL);
std::vector<t_point2i> data_points(NUM_DATA_POINTS);
std::vector<t_point2i> hull_points;
std::vector<t_convex_hull_builder*> builders = {
new t_graham_scan_convex_hull_builder(),
new t_line_wrap_convex_hull_builder(),
};
builders[1]->setup(data_points, hull_points);
builders[1]->build(data_points, hull_points);
for (unsigned int n = 0; n < builders.size(); n++) {
delete builders[n];
}
fclose(DATA_POINTS_FILE);
fclose(HULL_POINTS_FILE);
return 0;
}
/*--------------------------------------------------------*/
void AzOptOnTree_TreeReg::update_weight(int nx,
int fx,
double delta,
AzReg_TreeReg *reg)
{
double new_w = v_w.get(fx) + delta;
v_w.set(fx, new_w);
int dxs_num;
const int *dxs = data_points(fx, &dxs_num);
updatePred(dxs, dxs_num, delta, &v_p);
/*--- update the weight in the ensemble ---*/
const AzTrTreeFeatInfo *fp = tree_feat->featInfo(fx);
rgf_ens->tree_u(fp->tx)->setWeight(fp->nx, new_w);
reg->changeWeight(nx, delta);
}
/*--------------------------------------------------------*/
void AzOptOnTree::_refreshPred()
{
if (v_w.rowNum() == 0 && v_p.rowNum() == 0) return;
v_p.zeroOut();
v_p.set(var_const+fixed_const);
const double *w = v_w.point();
int f_num = v_w.rowNum();
int fx;
for (fx = 0; fx < f_num; ++fx) {
if (tree_feat->featInfo(fx)->isRemoved) continue;
int dxs_num;
const int *dxs = data_points(fx, &dxs_num);
updatePred(dxs, dxs_num, w[fx], &v_p);
}
}
/*--------------------------------------------------------*/
double AzOptOnTree_TreeReg::bestDelta(
int nx,
int fx,
AzReg_TreeReg *reg,
double nlam,
double nsig,
double py_avg,
AzRgf_forDelta *for_delta) /* updated */
const
{
const char *eyec = "AzOptOnTree_TI::bestDelta";
double w = v_w.get(fx);
int dxs_num;
const int *dxs = data_points(fx, &dxs_num);
if (dxs_num <= 0) {
throw new AzException(eyec, "no data indexes");
}
const double *fixed_dw = NULL;
if (!AzDvect::isNull(&v_fixed_dw)) fixed_dw = v_fixed_dw.point();
const double *p = v_p.point();
const double *y = v_y.point();
double nega_dL = 0, ddL= 0;
if (fixed_dw == NULL) {
AzLoss::sum_deriv(loss_type, dxs, dxs_num, p, y, py_avg,
nega_dL, ddL);
}
else {
AzLoss::sum_deriv_weighted(loss_type, dxs, dxs_num, p, y, fixed_dw, py_avg,
nega_dL, ddL);
}
double dR, ddR;
reg->penalty_deriv(nx, &dR, &ddR);
double dd = ddL + nlam*ddR;
if (dd == 0) dd = 1;
double delta = (nega_dL-nlam*dR)*eta/dd;
for_delta->check_delta(&delta, max_delta);
return delta;
}
/*--------------------------------------------------------*/
void AzOptOnTree::_update_with_features(
double nlam,
double nsig,
double py_avg,
AzRgf_forDelta *for_del) /* updated */
{
int fx;
int f_num = tree_feat->featNum();
for (fx = 0; fx < f_num; ++fx) {
if (tree_feat->featInfo(fx)->isRemoved) continue;
double w = v_w.get(fx);
int dxs_num;
const int *dxs = data_points(fx, &dxs_num);
double my_nlam = reg_depth->apply(nlam, node(fx)->depth);
double my_nsig = reg_depth->apply(nsig, node(fx)->depth);
double delta = getDelta(dxs, dxs_num, w, my_nlam, my_nsig, py_avg, for_del);
v_w.set(fx, w+delta);
updatePred(dxs, dxs_num, delta, &v_p);
}
}